Machine Learning Engineer

Jane Street Jane Street · Quant · New York, NY · Machine Learning

Jane Street is seeking a Machine Learning Engineer with a strong mathematical background to join their ML team and drive the direction of their ML platform. The role involves applying various ML techniques to aid decision-making in their trading environment, enhancing research workflows, and building/maintaining training and inference infrastructure to move concepts to production.

What you'd actually do

  1. Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
  2. A strong mathematical background; Good candidates will be excited about things like optimization theory, regularization techniques, linear algebra, and the like
  3. A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
  4. A proven ability to create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use
  5. Expertise wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow, or others

Skills

Required

  • Machine learning
  • mathematical foundations
  • ML ecosystem knowledge
  • neural networks
  • random forests
  • gradient-boosted trees
  • ensemble methods
  • optimization theory
  • regularization techniques
  • linear algebra
  • PyTorch
  • Jax
  • TensorFlow
  • building and maintaining training infrastructure
  • building and maintaining inference infrastructure
  • organized research codebase
  • reproducible results

Nice to have

  • curious mind
  • passion for solving interesting problems
  • inventive approach
  • willingness to ask hard questions

What the JD emphasized

  • robust, reproducible results
  • move from concept to production
  • state of the art

Other signals

  • ML platform development
  • enhancing research workflows
  • moving from concept to production